In many physical sciences, the most natural description of a system is with a function of position or time. In principle, infinitely many numbers are needed to specify that function, but in practice ...only finitely many measurements can be made. Inverse theory concerns the mathematical techniques that enable researchers to use the available information to build a model of the unknown system or to determine its essential properties. In Geophysical Inverse Theory, Robert Parker provides a systematic development of inverse theory at the graduate and professional level that emphasizes a rigorous yet practical solution of inverse problems, with examples from experimental observations in geomagnetism, seismology, gravity, electromagnetic sounding, and interpolation. Although illustrated with examples from geophysics, this book has broad implications for researchers in applied disciplines from materials science and engineering to astrophysics, oceanography, and meteorology. Parker's approach is to avoid artificial statistical constructs and to emphasize instead the reasonable assumptions researchers must make to reduce the ambiguity that inevitably arises in complex problems. The structure of the book follows a natural division in the subject into linear theory, in which the measured quantities are linear functionals of the unknown models, and nonlinear theory, which covers all other systems but is not nearly so well understood. The book covers model selection as well as techniques for drawing firm conclusions about the earth independent of any particular model.
The Sichuan Basin (SB) is one of the four most severely polluted regions in China in terms of air quality, and the frequent generation of temperature inversions is a key factor. The deep ...mountain-basin topography and the geographical location adjacent to the Tibetan Plateau combine to make the inversion characteristics of this region unique. Knowledge regarding these characteristics remains limited, however. In this study, the radiosonde data at standard pressure levels and significant levels from all SB operational radiosonde stations over 2015–2018 were used to document the climatological features of the inversions from the surface to a height of 5500 m and to evaluate the impact on local air pollutant concentrations.
Results revealed that the temperature inversion in the SB is a common and year-round phenomenon. The annual inversion frequency, depth, and strength values are 74.4%, 252.2 m, and 1.3 °C/100 m, respectively. The inversions are most frequent (95.4%), deepest (289.4 m), and strongest (1.6 °C/100 m) in winter. They tend to occur at one of two heights, either below 600 m or between 2200 and 3500 m. Based on their bottom heights, the inversions were divided into three groups: surface-based inversions (SIs), elevated inversions (EIs), and lower-troposphere inversions (LTIs). Annual LTI is most frequent (63.0%) and deepest (264.7 m), while annual SI is strongest (1.8 °C/100 m). Extreme contrasts exist in the seasonal properties of different inversion types. All types of inversions play a considerable role in air pollution, resulting in a high probability of severe and very serious pollution in winter. SI has a greater impact on pollutant concentrations than EI and LTI. The frequent generation of LTIs is a unique feature of the deep SB. LITs exert a significant impact on the formation of local heavy air pollution, but have not been given sufficient attention.
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•Inversions frequently occur below the height of 600 m and between 2200 and 3500 m.•The frequent generation of LTIs is a unique feature of the deep SB.•Annual LTIs are the most frequent and deepest, while annual SIs are the strongest.•LTIs, unnoticed in the past, have a significant impact on SB air pollution.
ABSTRACT
Tropospheric temperature inversions seem to be an important feature of climate, as well as a significant factor affecting air quality and fog formation. The aim of this article is to ...investigate the temporal and spatial variability of surface‐based inversions (SBIs) over Europe. It is based on data derived from the ERA‐Interim reanalysis for the period 1981–2015. The study examines diurnal, seasonal and multiannual variability of temperature inversions based on their frequency, depth and strength. These three parameters are characterized by strong temporal variability – diurnal and seasonal, as well as strong spatial differentiation. It has been confirmed that the energy budget is the key factor responsible for diurnal, and partly seasonal variability of SBI occurrence. Its negative values lead to an intense cooling of active surface and initiate the formation of the radiative inversions, which are the most common type of inversion occurring over the mainland of Europe. Temperature inversions usually form shortly after dusk, increasing gradually their depth and strength until sunrise. At 0000 Universal Time Coordinated (UTC), SBI frequency attains higher values in the summer than in the winter over the predominant part of Europe. However, the inversion layers occurring then are noticeably shallower and weaker. Surface type strongly affects SBI properties. This is mostly marked in terms of the distinct differentiation between marine and land areas as well as the impact of vast glaciers located across Greenland and western part of Iceland. Moreover, the distribution of SBI depth and strength is shaped by atmospheric circulation. For instance, their higher values occur over Eastern Europe in the winter, which is associated with the influence of a seasonal high pressure system found over Russia. Taking into account multiannual variability, SBI parameters, primarily depth and strength, exhibit the most significant negative changes in the winter.
Diurnal and seasonal variability of the mean frequency (%) of surface‐based inversions in the years 1981–2015. Black isolines indicate equal hours before and after sunrise at 0600 UTC and before and after sunset at 1800 UTC. The isolines were generated for winter (DJF) on January 15th, spring (MAM) on April 15th, summer (JJA) on July 15th and autumn (SON) on October 15th, respectively.
Tropospheric temperature inversions are thought to be an important feature of climate as well as a significant factor affecting air quality and low‐level cloud formation. The aim of this study is to ...investigate the temporal and spatial variability of the tropospheric temperature inversions, in particular so‐called elevated inversions, over Europe. The analysis is based on data gained from ERA‐Interim reanalysis for the period 1981–2015. The data consist of air temperature, and geopotential height from the entire vertical cross‐section of the troposphere, that is, from 1,000 to 100 hPa. The study examines the temporal (intra‐ and inter‐annual) variability of the temperature inversions based on their frequency, base height, depth, and strength. The analysis conducted revealed that the temperature inversions are a common phenomenon occurring in the lower troposphere. Their temporal and spatial variability is, however, determined by the inversion type. Surface‐based inversions (SBI) indicate a clear diurnal cycle, while the day–night variability of elevated inversions (EI) is far less pronounced. Two main regions of the most frequent EI occurrence may be distinguished. These are: (a) a marine area west of the Iberian Peninsula and (b) Eastern Europe. Both of them are located in areas which are under the influence of extensive high‐pressure systems—the permanent Azores High and semipermanent Siberian High, respectively. The development of EI should be therefore attributed to the large‐scale subsidence and adiabatic heating of air parcels. EI are also quite common over the other parts of the Atlantic Ocean, which is closely linked to the development of marine inversions. SBI tend to be stronger than EI—the mean seasonal inversion strength is usually substantially higher for SBI. In turn, EI reach higher values of the mean seasonal inversion depth as compared with SBI.
The temperature inversions are a common phenomenon occurring in the lower troposphere. Their temporal and spatial variability is, however, determined by the inversion type. Surface‐based inversions (SBI) indicate a clear diurnal cycle, while the day–night variability of elevated inversions (EI) is far less pronounced. The analysis conducted revealed that anticyclonic circulation is both an important factor supporting the subsidence leading to EI occurrence and a good precursor of the nocturnal radiation favourable for the development of deep SBI.
Temperature inversion tends to inhibit the transfer of momentum, heat and moisture in the atmospheric boundary layer, which is often accompanied by severe air pollution. Recently, severe haze ...pollution has frequently occurred in North China. In this study, the characteristics of temperature inversion on severe polluted days (SPDs) in Beijing were investigated by using radiosonde data with standard pressure levels from 2011 to 2016. Both surface-based inversion (SI) and elevated inversion (EI) were analyzed. 93% of the SPDs were accompanied by temperature inversion, most of which occurred in wintertime. Annual frequency of SI (FSI) and EI (FEI) showed slight fluctuations with mean value of 0.18 and 0.67, respectively. Overall, the annual SI was stronger and deeper than annual EI. Seasonally, the SI was most frequent (0.39) in autumn, in contrast to EI that occurred most frequently (0.95) in summer. Both SI and EI were weakest in summer and strongest in winter. Average monthly SI strength was about 0.38 °C in summer and 2.40 °C in winter, average monthly EI strength was about 0.64 °C in summer and 2.20 °C in winter. The average monthly SI and EI were deepest in winter and shallowest in summer. SI depth were 778 m and 221 m in winter and summer, EI were 630 m and 336 m in winter and summer. The substantially strong liner relationship was found between seasonal inversion strength and PM2.5 concentration, and the inversion strength was found to be better compared with the inversion depth at predicting the PM2.5 concentration during SPDs. Obvious lower air outflow and turbulent kinetic energy were found in SPDs compared to non-SPDs, which indicated weaker turbulence in SPDs. Future efforts should focus on accurate model simulations of temperature inversions in SPDs.
Figure 7 Seasonal variation of PM2.5 concentration and inversion strength in SPDs and non-SPDs. The inversion strength was found to be better compared with the inversion depth at predicting the PM2.5 concentration during SPDs. Display omitted
•This study is the first analysis of temperature inversion during SPDs.•93% of SPDs were accompanied by inversion, most of which occurred in wintertime.•Inversions were strongest and deepest in winter, weakest and shallowest in summer.•The inversion strength was better at predicting PM2.5 concentration during SPDs.•Obvious lower air outflow and turbulent kinetic energy were found in SPDs.
Temperature inversions inhibit the transfer of momentum, heat and moisture in the atmosphere and have led to severe air pollution in China. This study investigated the spatiotemporal variation in ...temperature inversions in China using sounding data for the past four decades. Surface-based inversion, elevated inversion, and both in one sounding dataset were analysed. Statistical analyses of inversion parameters included frequency, strength and depth. The annual frequency of total inversions showed no significant increasing or decreasing trend with mean values of 0.78, 0.33, 0.24, 0.28, 0.5 and 0.36 at six stations representing different climate zones-Beijing, Harbin, Haikou, Shaowu, Ruoqiang, and Xining, respectively. The annual inversion strength and depth showed downward trends. Monthly variation in inversion frequency and strength differed among stations. The weakest surface-based inversion was found in summer at Beijing and Harbin with mean values of 1 and 1.3 °C, respectively; the strongest surface-based inversion was found in winter with respective mean values of 3.5 and 3.6 °C. Higher surface temperature in summer and subsidence aloft in winter may explain the monthly variation in inversion depth with a minimum in summer, with mean values of 165, 334, 135, 267, 363 and 420 m, and a maximum in winter, with mean values of 250, 646, 140, 591, 806 and 664 m, at the six respective stations. Total inversion was least frequent in southwestern China (mean 0.15), surface-based inversion was most frequent in the north (mean 0.78), and elevated inversion was most frequent in the southeast (mean 0.42). The strongest, deepest surface-based inversion dominated in the north (mean 3.4 °C and 398 m). Elevated inversion strength did not significantly differ among regions (mean 2.5 °C). The deepest elevated inversion dominated in the southeast (mean 654 m). Future efforts should focus on the interactions between aerosols and temperature inversions and accurate model simulations of temperature inversions.
The targeted deletion, replacement, integration or inversion of genomic sequences could be used to study or treat human genetic diseases, but existing methods typically require double-strand DNA ...breaks (DSBs) that lead to undesired consequences, including uncontrolled indel mixtures and chromosomal abnormalities. Here we describe twin prime editing (twinPE), a DSB-independent method that uses a prime editor protein and two prime editing guide RNAs (pegRNAs) for the programmable replacement or excision of DNA sequences at endogenous human genomic sites. The two pegRNAs template the synthesis of complementary DNA flaps on opposing strands of genomic DNA, which replace the endogenous DNA sequence between the prime-editor-induced nick sites. When combined with a site-specific serine recombinase, twinPE enabled targeted integration of gene-sized DNA plasmids (>5,000 bp) and targeted sequence inversions of 40 kb in human cells. TwinPE expands the capabilities of precision gene editing and might synergize with other tools for the correction or complementation of large or complex human pathogenic alleles.
Wavefield reconstruction inversion (WRI) formulates a PDE-constrained optimization problem to reduce cycle skipping in full-waveform inversion (FWI). WRI is often implemented by solving for the ...frequency-domain representation of the wavefield using the finite-difference method. The approach requires matrix inversions and affords limited flexibility to accommodate irregular model geometries. On the other hand, the physics-informed neural network (PINN) uses the underlying physical laws as loss functions to train the neural network (NN) to provide flexible continuous functional approximations of the solutions without matrix inversions. By including a data-constrained term in the loss function, the trained NN can reconstruct a wavefield that simultaneously fits the recorded data and satisfies the Helmholtz equation for a given initial velocity model. Using the predicted wavefields, we rely on a small-size NN to predict the velocity using the reconstructed wavefield. In this velocity prediction NN, spatial coordinates are used as input data to the network, and the scattered Helmholtz equation is used to define the loss function. After we train this network, we are able to predict the velocity in the domain of interest. We develop this PINN-based WRI method and demonstrate its potential using a part of the Sigsbee2A model and a modified Marmousi model. The results show that the PINN-based WRI is able to invert for a reasonable velocity with very limited iterations and frequencies, which can be used in a subsequent FWI application.
This article describes a robust simultaneous joint inversion scheme for the interpretation of gravity and self-potential data measured along the profile. The developed scheme jointly inverts the two ...data sets of the causative targets by some geometrically simple idealized bodies (the so-called approximative/interpretive models) in the restricted class of spheres and cylinders. It simultaneously recovers the characteristic inverse parameters of all interpretive bodies (that is, the depth <inline-formula> <tex-math notation="LaTeX">z </tex-math></inline-formula>, amplitude coefficient <inline-formula> <tex-math notation="LaTeX">A </tex-math></inline-formula>, electric dipole moment <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula>, and polarization angle <inline-formula> <tex-math notation="LaTeX">\theta </tex-math></inline-formula> of each body). It employs the Gauss-Newton (GN) method in the space of the logarithmed and nonlogarithmed model parameters (<inline-formula> <tex-math notation="LaTeX">\log (|A|) </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\log (K) </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\theta </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\log (z) </tex-math></inline-formula> of each body) (rather than in the space of the model parameters themselves (<inline-formula> <tex-math notation="LaTeX">A </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">\theta </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">z </tex-math></inline-formula>)) to maintain the convergence. The scheme has been successfully validated on a number of noise-free numerical examples, after which the accuracy and stability of the scheme have been carefully assessed on various noisy data. The influence of the scaling factors of the objective functional subjected to minimization on the convergence of the GN method and on the nonuniqueness of the approximative solution that describes and resembles the underlying buried targets has been investigated. It has been found that the developed scheme is very robust and capable of extracting accurate and useful information that is of some significance in mineral exploration. Finally, the scheme has been applied to a real data example from Germany. Careful analysis of this case study suggests new results that are of some value in mining geophysics.
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